For long-haul telecommunication service providers, access is a key component of the total cost. Whether the service is the classic time division multiplexed (TDM) service or modern packet services (e.g. ATM, Frame, or IP), often a significant portion of the end-to-end cost will be related to the access circuits. Access circuits connect end customer locations to the long-haul service provider's point of presence (pop). In most cases, the long-haul service provider (who generally is the end-to-end service provider) leases access circuits from third party suppliers. Before telecom deregulation was a world-wide phenomenon (over a decade or so ago), access providers were monopolies (in most situations, government owned). However, with rapid telecom deregulation happening in most countries in the world, access supply has become quite competitive. However, for players in the access arena, access supply may not be universal (that is, access may not be available by a given supplier in all geographical regions of a given country). Also, the tariff structures followed by the supplier may be complex, geography dependent, and may not be uniform. Almost invariably, access suppliers bundle circuits in different ways. Quite often, long-haul service providers seek quotes or (RFP responses) from access providers and attempt to choose the best suppliers in a country or region. When multiple overlapping bundles are present and circuit volume is large, manual analysis is typically not able to produce optimal suppliers for all circuits. Moreover, manual analysis requires significant time and resources and quickly becomes impractical as circuit volume and number of potential suppliers increase. Hence, there is a need for automated methods and associated apparatus to model various access cost scenarios in calibration with supplier responses. The present invention addresses this problem in a novel manner.
The problem solved by this invention is faced by long haul providers, access providers, and enterprise carriers in telecom; and also by many end customers. The fundamentals of this invention are applicable to any RFP response evaluations, where complex responses need to be processed quickly and efficiently.
Evaluating RFP responses for choosing the best access suppliers is a complex process. There are many factors that need to be taken into consideration. Telecom carriers look for access suppliers to lease access circuits in regions where their own network can not reach end customers cost effectively.
Access circuit leasing cost represents the dominant portion of the total cost of providing telecom services to end customers in some cases. To reduce access circuit leasing cost, carriers routinely ask all potential suppliers to bid on existing access circuit inventory via the RFP process. These RFP responses are analyzed to identify best suppliers for access circuits.
The circuit volume and complexity in RFP responses make it very difficult to identify optimal suppliers effectively. In many cases, suppliers provide bid pricing in circuit bundles where the pricing applies only if the suppliers are awarded all circuits in the bundle. Additionally, there is no standard for how suppliers bundle and present their circuits. Different suppliers may bundle circuits in totally different ways. Complexity increases as well in determining the lowest cost carrier due to comparing bundles that may or may not overlap among suppliers. These factors introduce significant combinatorial complexities in choosing the lowest cost supplier from the submitted RFP bids.